Knowledge discovery in unstructured, big data
Knowledge may be discovered from various sources of information. Knowledge Discovery in Database (KDD) is the process of discovering valuable knowledge from data collection. Data warehousing, traditional data processing and analysis of structured data through the Relationship Database Management Sys...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Online Access: | http://psasir.upm.edu.my/id/eprint/39244/ http://psasir.upm.edu.my/id/eprint/39244/1/39244.pdf |
| Summary: | Knowledge may be discovered from various sources of information. Knowledge Discovery in Database (KDD) is the process of discovering valuable knowledge from data collection. Data warehousing, traditional data processing and analysis of structured data through the Relationship Database Management System (RDBMS) is access to a standard IT technology. However, RDBMS cannot satisfy the challenges of Big Data. The current biggest challenge is a matter of turning Big Data into Knowledge Discovery insight that enable organizations to facilitate effective decision making. The purpose of this paper is to explore techniques in knowledge discovery and the challenges in Big Data real-time setting. A technique of knowledge discovery in real-time insight will be proposed in order to extract valuable knowledge. |
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